Jalostuksen ja maantieteen vaikutus koirarotujen erilaistumisessa geneettisiksi osapopulaatioiksi
Why this work is in the frame
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Bibliographic record
Abstract
Purebred dogs can be fragmented into within-breed subpopulations based on their geographical location and divergent selection regimes.This stratification has significance for breeding, when the subpopulations are also genetically differentiated from each other.Problems of inbreeding, such as specific genetic disorders, can accumulate within the genetic subpopulations.Therefore, identifying the genetic subpopulations and their causes can help to conserve genetic diversity and health of a dog breed.In this study, six dog breeds were analysed for the occurrence of genetic differentiation to subpopulations.This differentiation was measured by performing a genome-wide survey of 1319 single nucleotide polymorphism (SNP) markers from 142 Belgian Shepherd, 104 English Greyhound, 224 Finnish Lapphund, 90 Italian Greyhound, 608 Labrador Retriever and 95 Shetland Sheepdog.In order to find a selection-related explanation to the genetic differentiation, I compared the observed subpopulations to the individual's data about their geographical origin or breeding line.I discovered that all the breeds studied are fragmented into genetic subpopulations.The geographical origin explained the findings of the Italian Greyhound and the Shetland Sheepdog.The selection for performance explained the genetic subpopulations in the English Greyhound and in the Labrador Retriever.The morphological selection was a plausible explanation in the Belgian Shepherd and in the Finnish Lapphund.Additionally, evidence of the overlapping explanations to the genetic subpopulation differentiation was found in the Belgian Shepherd, the English Greyhound, the Italian Greyhound and the Labrador Retriever.It is probable that all the breeds studied would benefit if the findings of the genetic subpopulations were considered in their breeding program.Evidence of the genetic subpopulations within the dog breeds was convincing and therefore similar surveys for other dog breeds are recommendable.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it